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Title: sklearn-tree-BN-knn Download
  • Category:
  • Data Mining
  • Tags:
  • File Size:
  • 1.24mb
  • Update:
  • 2019-03-31
  • Downloads:
  • 0 Times
  • Uploaded by:
  • Ryan112
 Description: Performance comparison and optimization of classifiers: We use tree, Bayesian and KNN in scikit-learnpackage to train the data model and try to understand its principle and application. The performances of three classifiers are compared and their characteristics are analyzed. The data set used in this experiment is house and segment.
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FilenameSizeDate
lab3 0  2019-03-31

lab3\GaussianNB-house-matplotlib.png 15026  2019-03-22

lab3\GaussianNB-segment-matplotlib.png 30364  2019-03-21

lab3\house-votes-84.data 18171  2016-03-16

lab3\house-votes-84.names 7059  2016-03-16

lab3\knn-house-matplotlib.png 15725  2019-03-22

lab3\knn-house.py 5523  2019-03-22

lab3\knn-segment-matplotlib.png 29129  2019-03-22

lab3\knn-segment.py 5546  2019-03-22

lab3\MultinomialNB-house-matplotlib.png 14986  2019-03-22

lab3\MultinomialNB-segment-matplotlib.png 31075  2019-03-21

lab3\naive-bayes-house.py 4183  2019-03-21

lab3\naive-bayes-segment.py 5368  2019-03-21

lab3\segment-tain.txt 200410  2007-10-11

lab3\segment-test.txt 109984  2007-10-11

lab3\tree-house-graphviz.dot 1453  2019-03-22

lab3\tree-house-graphviz.png 75493  2019-03-22

lab3\tree-house-matplotlib.png 16219  2019-03-22

lab3\tree-house.py 5870  2019-03-22

lab3\tree-segment-graphviz.dot 17529  2019-03-22

lab3\tree-segment-graphviz.png 1011689  2019-03-22

lab3\tree-segment-matplotlib.png 41287  2019-03-22

lab3\tree-segment.py 6706  2019-03-22

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